PREVALENCE OF RISK FACTORS OF CARDIOVASCULAR DISEASES AND RISK PROFILING AMONG INDIVIDUALS IN A SOUTH INDIAN CITY- A COMMUNITY BASED CROSS SECTIONAL STUDY

• Neha Nagaraj,  
• Gopinath S*

Abstract

Background: The global demographic and epidemiological transitions are increasing the burden of non-communicable diseases, with cardiovascular diseases (CVD) being the leading cause of mortality. Due to limited risk estimation studies in India, this study was conducted to address this gap, following the WHO's risk approach for CVD prevention. The aim is to estimate the prevalence of cardiovascular disease risk factors and predict CVD risk among study subjects using a modified WHO STEPS questionnaire and WHO/ISH risk charts. Methodology: A community-based cross-sectional study was conducted in a South Indian city from January 2021 to November 2022 with a sample size of 180, using the WHO/ISH risk prediction tool to assess CVD risk factors. Data analysis was performed with Microsoft Excel and SPSS 21, using descriptive analysis for baseline demographics, Chi-square tests for associations, and multinomial logistic regression to identify independent CVD risk factors. Results: The most prevalent risk factors were hypertension (36.9%), obesity (27.8%), dyslipidemia (27.7%), diabetes mellitus (21.7%), low physical activity (15.7%), smoking (13.1%), and alcohol intake (12.1%). Among participants, 16.5% had a high (>20%), 16% had a moderate (10-20%), and 67.5% had a low (40 years, dyslipidemia, physical inactivity, junk food consumption, smoking, diabetes mellitus, and hypertension. In the multinomial logistic regression model, age, physical inactivity, diabetes, and hypertension were significant predictors for both high and moderate risk. Conclusion: Our study found a higher proportion of participants with high cardiovascular risk, with physical inactivity, diabetes mellitus, and hypertension being significant predictors, and diabetes mellitus having the highest odds. The WHO/ISH chart proved useful for estimating CVD risk in resource-limited settings.

Keywords

Cardiovascular diseases, WHO/ISH risk prediction tool, risk factors, CVD risk